Sharif Digital Repository

This paper addresses the problem of robust parameter estimation of simple linear profiles in multistage processes in the presence of outliers in Phase I. In this regard, two robust approaches, namely the Huber’s M-estimator and the MM estimator, are proposed to estimate the parameters of the process in Phase I in the presence of outliers in historical data. In addition, the U statistic is applied to the robust parameter estimates to remove the effect of the cascade property in multistage processes and as a result, to obtain adjusted robust estimates of the parameters of simple linear profiles. The performance of the proposed methods is evaluated under weak and strong autocorrelations... 

This paper addresses the problem of robust parameter estimation of simple linear profiles in multistage processes in the presence of outliers in Phase I. In this regard, two robust approaches, namely the Huber’s M-estimator and the MM estimator, are proposed to estimate the parameters of the process in Phase I in the presence of outliers in historical data. In addition, the U statistic is applied to the robust parameter estimates to remove the effect of the cascade property in multistage processes and as a result, to obtain adjusted robust estimates of the parameters of simple linear profiles. The performance of the proposed methods is evaluated under weak and strong autocorrelations... 

In this paper a new probabilistic view to the Visual Secret Sharing (VSS) is presented and as a result, a new VSS scheme is proposed. The proposed scheme is a threshold scheme with perfect black pixel reconstruction. We present the scheme by introducing two sets C0 and C1. We consider an unknown probability distribution on the elements of C0 and C 1. Perfectness provides some linear constraints on the probabilities of C0 and C1 elements. By solving the provided system of linear equations, the probability distributions are specified and we achieve a perfect VSS scheme. ©2008 IEEE  

The ABS methods, introduced by Abaffy, Broyden and Spedicato, are direct iteration methods for solving a linear system where the ith iterate satisfies the first i equations, therefore a system of m equations is solved in at most m steps. Recently, we have presented a new approach to devise a class of ABS-type methods for solving full row rank systems [K. Amini, N. Mahdavi-Amiri, M. R. Peyghami, ABS-type methods for solving full row rank linear systems using a new rank two update, Bulletin of the Australian Mathematical Society 69 (2004) 17-31], the ith iterate of which solves the first 2i equations. Here, to reduce the space and computation time, we use a new extended rank two update formula... 

In this paper, a new algorithm for Sparse Component Analysis (SCA) or atomic decomposition on over-complete dictionaries is presented. The algorithm is essentially a method for obtaining sufficiently sparse solutions of underdetermined systems of linear equations. The solution obtained by the proposed algorithm is compared with the minimum ℓ1-norm solution achieved by Linear Programming (LP). It is experimentally shown that the proposed algorithm is about two orders of magnitude faster than the state-of-the-art ℓ1-magic, while providing the same (or better) accuracy. © Springer-Verlag Berlin Heidelberg 2007  

This paper addresses the problem of robust parameter estimation of simple linear profiles in multistage processes in the presence of outliers in Phase I. In this regard, two robust approaches, namely the Huber’s M-estimator and the MM estimator, are proposed to estimate the parameters of the process in Phase I in the presence of outliers in historical data. In addition, the U statistic is applied to the robust parameter estimates to remove the effect of the cascade property in multistage processes and as a result, to obtain adjusted robust estimates of the parameters of simple linear profiles. The performance of the proposed methods is evaluated under weak and strong autocorrelations... 

The state-space averaging applied to switched networks generally results in nonlinear systems. It is common to perform a small signal linearization about an operating point to obtain a linear system. When the variations in signals are large, e.g., in PFC rectifiers, the small signal approximation produces results that are susceptible to instability problems. In this paper a class of piecewise linear models merged by fuzzy system are introduced for PWM converters. The necessary and sufficient and conditions for stability of fuzzy models using fuzzy state-feedback controllers are given. The results obtained are illustrated with a buck-boost converter. The simulation and experimental results... 

Using a non-linear model in model predictive control (MPC) changes the control problem from a convex quadratic programme to a non-convex non-linear problem, which is much more challenging to solve. In this study, we introduce an MPC algorithm for non-linear discrete-time systems. The systems are composed of a linear constant part perturbed by an additive state-dependent non-linear term. The control objective is to design a state-feedback control law that minimises an infinite horizon cost function within the framework of linear matrix inequalities. In particular, it is shown that the solution of the optimisation problem can stabilise the non-linear plants. Three extensions, namely,... 

Linear controllers have been widely used for controlling Active Power Filters (APFs). However, due to their limitations, a tradeoff between the bandwidth of the current control loop (CCL) and the voltage control loop (VCL) need to be made to remain stable in all conditions. This tradeoff leads to imperfect usage of the APF's capacity. Nonlinear controllers can eliminate such limitations and simultaneously remain stable in all conditions. In this paper, a new nonlinear controller for controlling the output current and the DC voltage (Vdc) of an APF is proposed. Feedback linearization method is applied on the CCL and the VCL is controlled via indirect method. In this method, an auxiliary... 

Synthetic inertial frequency response has attracted increasing attention due to the paradigm shift in power generation from synchronous generators toward wind turbines. This paper presents a novel nonlinear controller to enable inertial response of a variable speed wind turbine (VSWT). The VSWT has a nonlinear model which cannot efficiently be dealt with by linear control techniques as it may experience large deviations from its operating point during the frequency support period. To design the controller, a nonlinear model for the wind turbine together with power system is utilized. The output power of the wind turbine is expressed in terms of the state variables, and its exact Taylor... 

In this study a new nonlinear control approach is introduced to suppress libration of a tethered satellite system (TSS). It benefits from coupling between satellites and tether libration dynamics. The control concept uses the main satellite attitude maneuvers to suppress librational motion of the tether. To achieve this goal, the main satellite attitude control actuators are used as the only actuation in the system. The study considers planar motion of a two body TSS system in a circular orbit. Governing dynamic equations of motion are derived using extended Lagrange method. Controllability of the system about equilibrium state is studied and a nonlinear controller is designed using feedback... 

This paper deals with the stabilization of the feasible equilibrium point of a special class of nonlinear quadratic systems known as Lotka-Volterra (LV) systems, in the presence of interval uncertainty via a fixed linear state feedback (FLSF). It is well known that for a linear time-invariant system with interval uncertainty, stability at the vertices of a polytope implies stability in the interior of the whole polytope. It has been shown that this idea can be extended to examine the stability of LV systems in the presence of interval uncertainty, recently. In fact, it has been proved that in spite of nonlinear nature of the system, stability at a special vertex guarantees stability at all... 

Reinforcement learning methods such as Q-learning have shown promising results in the model-free design of linear quadratic regulator (LQR) controllers for linear time-invariant (LTI) systems. However, challenges such as sample-efficiency, sensitivity to hyper-parameters, and compatibility with classical control paradigms limit the integration of such algorithms in critical control applications. This paper aims to take some steps towards bridging the well-known classical control requirements and learning algorithms by using optimization frameworks and properties of conic constraints. Accordingly, a new off-policy model-free approach is proposed for learning the Q-function and designing the... 

In this research study, chaos control of continuous time systems has been performed by using dynamic programming technique. In the first step by crossing the response orbits with a selected Poincare section and subsequently applying linear regression method, the continuous time system is converted to a discrete type. Then, by solving the Riccati equation a sub-optimal algorithm has been devised for the obtained discrete chaotic systems. In the next step, by implementing the acquired algorithm on the quantized continuous time system, the chaos has been suppressed in the Rossler and AFM systems as some case studies  

The objective of this work is to create an analytical framework to study the problem of squeezed film damping in micromirrors considering the bending of the supporting torsion microbeams. Using mathematical and physical justifications, nonlinear Reynolds equation governing the behavior of the squeezed gas underneath the mirror is linearized. The resulting linearized equation is then nondimensionalized and analytically solved for two cases of the infinitesimal and finite tilting angle of the mirror. The obtained pressure distribution from the solution of the Reynolds equation is then utilized for finding the squeezed film damping force and torque applied to the mirror. The results show that... 

This paper presents a new method for tuning linear controllers such as Proportional-Integrating (PI) and Proportional-Resonant (PR) structures which are frequently used in different power electronic and power system applications. Those controllers are placed within a general structure offered by the Internal Model Principle (IMP) of control theory. In this paper, the first perspective uses the well-known concept of Linear Quadratic Regulator (LQR) to address the problem as a regulation problem. Matrix Q of the LQR design is then finely adjusted in order to assure desired transient response for the system. The second perspective is based on redefining the LQR problem in order to make it... 

We study the problem of approximating a function F:ℝ → ℝ by a piecewise-linear function F̄ when the values of F at {x 1,...,xn} are given by a discrete probability distribution. Thus, for each xi we are given a discrete set y i,1,..., yi,mi of possible function values with associated probabilities pi,j such that Pr[F(xi) = yi,j] = pi,j. We define the error of F̄ as error(F, F̄) = maxi=1n E[|Fxi) - F̄(xi)|]. Let m = ∑i=1nmi be the total number of potential values over all F(xi). We obtain the following two results: (i) an O(m) algorithm that, given F and a maximum error ε, computes a function F̄ with the minimum number of links such that error(F, F̄) ≤ ε; (ii) an O(n4/3+δ + mlogn) algorithm... 

In this study tracking problem of tip of a micro cantilever, actuated by electrostatic, is investigated. Dynamic model of the system is a PDE. Using electrostatic actuation introduced significant nonlinearity in dynamic model of the system. Control goals are achieved by means of backstepping for SI and feedback linearization for MI system. Performance of control system is inspected for some assumptions and simplifications. The results are in according to numerical simulations  

This paper addresses the problem of optimal state-feedback design for a class of non-linear systems. The method is applicable to all non-linear systems which can be linearised using the method of state-feedback linearisation. The alternative is to use linear optimisation techniques for the linearised equations, but then there is no guarantee that the original non-linear system behaves optimally. The authors use feedback linearisation technique to linearise the system and then design a state feedback for the feedback-linearised system in such a way that it ensures optimal performance of the original non-linear system. The method cannot ensure global optimality of the solution but the global...